INFEWS/T1: Impacts of Deglobalization on the Sustainability of Regional Food, Energy, Water Systems

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Increased globalization through international trade, migration, and technological innovation has generated substantial wealth in the U.S. economy over the past 50 years. These gains , however, have been accompanied by job losses in the manufacturing sector, growing wealth inequality in society and environmental impacts abroad. Counter social and political trends reveal a potential for deglobalization, i.e., diminished integration of the U.S. with global markets. The goal of this project is to examine the potential effects of deglobalization on the sustainability of regional food-energy-water systems (FEWS) and well-being of FEW producers and consumers. We develop a new integrated modeling framework that accounts for individual land use and management decisions, regional demands for land, energy and water resources, and water quality and greenhouse gas emissions impacts. We apply the model to a five-state Great Lakes region: Illinois, Indiana, Michigan, Ohio, and Wisconsin and evaluate the implications of varying future deglobalization scenarios and policies for regional FEWS sustainability and societal well-being. Local and regional stakeholders are engaged throughout the research process via a participatory modeling approach to guide model specification, develop future scenarios, and identify sustainability metrics. The research results are used to guide discussion of potential Great Lakes regional futures with policymakers and other stakeholders. The modeling framework builds from a Dynamic Stochastic General Equilibrium model that accounts for both the time evolution of key resource stocks and the behavioral dynamics of individuals. The model quantifies the effects of uncertain future changes in environmental, economic, or policy conditions at national and global scales on the regional production of food and energy services that use land, water, and energy resources and that depend on farmer, land use, and watershed heterogeneity. We account for these local heterogeneities using individual farmer behavioral and spatially explicit land data from the Maumee River basin. By creating a dynamic stochastic integrated modeling framework that also accounts for individual decision making and spatial land use-watershed heterogeneity, this research advances the integrated modeling of regional FEWS. The research team also devises a novel approach to sustainability assessment that builds on the unique features of the Dynamic Regional Food, Energy, Water Systems modeling framework to identify policies that are robust in achieving desirable outcomes under a range of uncertainty conditions. The participatory modeling approach with stakeholders improves model validity and generates innovations in how scientific knowledge is created, disseminated, and applied to the management of regional FEWS with specific application to the Great Lakes region.